Overview

Dataset statistics

Number of variables21
Number of observations173
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.5 KiB
Average record size in memory168.7 B

Variable types

NUM19
CAT2

Warnings

Women is highly correlated with Total and 6 other fieldsHigh correlation
Total is highly correlated with Women and 8 other fieldsHigh correlation
Sample_size is highly correlated with Total and 5 other fieldsHigh correlation
Employed is highly correlated with Total and 8 other fieldsHigh correlation
Full_time is highly correlated with Total and 8 other fieldsHigh correlation
Part_time is highly correlated with Total and 6 other fieldsHigh correlation
Full_time_year_round is highly correlated with Total and 6 other fieldsHigh correlation
Unemployed is highly correlated with Total and 8 other fieldsHigh correlation
P75th is highly correlated with MedianHigh correlation
Median is highly correlated with P75thHigh correlation
Non_college_jobs is highly correlated with Total and 7 other fieldsHigh correlation
Low_wage_jobs is highly correlated with Total and 6 other fieldsHigh correlation
Rank has unique values Unique
Major_code has unique values Unique
Major has unique values Unique
Full_time has unique values Unique
Full_time_year_round has unique values Unique
College_jobs has unique values Unique
Non_college_jobs has unique values Unique
Part_time has 3 (1.7%) zeros Zeros
Unemployed has 5 (2.9%) zeros Zeros
Unemployment_rate has 5 (2.9%) zeros Zeros
Low_wage_jobs has 5 (2.9%) zeros Zeros

Reproduction

Analysis started2022-10-21 14:36:24.019305
Analysis finished2022-10-21 14:37:06.417754
Duration42.4 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Rank
Real number (ℝ≥0)

UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87
Minimum1
Maximum173
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:06.523316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.6
Q144
median87
Q3130
95-th percentile164.4
Maximum173
Range172
Interquartile range (IQR)86

Descriptive statistics

Standard deviation50.08492787
Coefficient of variation (CV)0.5756888261
Kurtosis-1.2
Mean87
Median Absolute Deviation (MAD)43
Skewness0
Sum15051
Variance2508.5
MonotocityStrictly increasing
2022-10-21T10:37:06.643371image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
110.6%
 
12010.6%
 
11210.6%
 
11310.6%
 
11410.6%
 
11510.6%
 
11610.6%
 
11710.6%
 
11810.6%
 
11910.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
110.6%
 
210.6%
 
310.6%
 
410.6%
 
510.6%
 
ValueCountFrequency (%) 
17310.6%
 
17210.6%
 
17110.6%
 
17010.6%
 
16910.6%
 

Major_code
Real number (ℝ≥0)

UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3879.815029
Minimum1100
Maximum6403
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:06.771554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1100
5-th percentile1301.6
Q12403
median3608
Q35503
95-th percentile6205.4
Maximum6403
Range5303
Interquartile range (IQR)3100

Descriptive statistics

Standard deviation1687.75314
Coefficient of variation (CV)0.435008661
Kurtosis-1.475186702
Mean3879.815029
Median Absolute Deviation (MAD)1400
Skewness0.05549824531
Sum671208
Variance2848510.663
MonotocityNot monotonic
2022-10-21T10:37:06.897305image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
241910.6%
 
230510.6%
 
130210.6%
 
110610.6%
 
230010.6%
 
640210.6%
 
260210.6%
 
400110.6%
 
231110.6%
 
611010.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
110010.6%
 
110110.6%
 
110210.6%
 
110310.6%
 
110410.6%
 
ValueCountFrequency (%) 
640310.6%
 
640210.6%
 
629910.6%
 
621210.6%
 
621110.6%
 

Major
Categorical

UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
PETROLEUM ENGINEERING
 
1
MATHEMATICS TEACHER EDUCATION
 
1
FORESTRY
 
1
SOIL SCIENCE
 
1
GENERAL EDUCATION
 
1
Other values (168)
168 
ValueCountFrequency (%) 
PETROLEUM ENGINEERING10.6%
 
MATHEMATICS TEACHER EDUCATION10.6%
 
FORESTRY10.6%
 
SOIL SCIENCE10.6%
 
GENERAL EDUCATION10.6%
 
HISTORY10.6%
 
FRENCH GERMAN LATIN AND OTHER COMMON FOREIGN LANGUAGE STUDIES10.6%
 
INTERCULTURAL AND INTERNATIONAL STUDIES10.6%
 
SOCIAL SCIENCE OR HISTORY TEACHER EDUCATION10.6%
 
COMMUNITY AND PUBLIC HEALTH10.6%
 
Other values (163)16394.2%
 
2022-10-21T10:37:07.034522image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique173 ?
Unique (%)100.0%
2022-10-21T10:37:07.164824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length65
Median length24
Mean length25.31213873
Min length5

Total
Real number (ℝ≥0)

HIGH CORRELATION

Distinct172
Distinct (%)100.0%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean39370.0814
Minimum124
Maximum393735
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:07.285275image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum124
5-th percentile1125.5
Q14549.75
median15104
Q338909.75
95-th percentile188044.4
Maximum393735
Range393611
Interquartile range (IQR)34360

Descriptive statistics

Standard deviation63483.49101
Coefficient of variation (CV)1.612480563
Kurtosis9.379324238
Mean39370.0814
Median Absolute Deviation (MAD)12154.5
Skewness2.87683411
Sum6771654
Variance4030153631
MonotocityNot monotonic
2022-10-21T10:37:07.404113image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
233910.6%
 
1423710.6%
 
360710.6%
 
68510.6%
 
14371810.6%
 
14195110.6%
 
4824610.6%
 
2465010.6%
 
2019810.6%
 
1973510.6%
 
Other values (162)16293.6%
 
ValueCountFrequency (%) 
12410.6%
 
60910.6%
 
68510.6%
 
72010.6%
 
75610.6%
 
ValueCountFrequency (%) 
39373510.6%
 
32992710.6%
 
28070910.6%
 
23459010.6%
 
21399610.6%
 

Men
Real number (ℝ≥0)

Distinct172
Distinct (%)100.0%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean16723.40698
Minimum119
Maximum173809
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:07.532170image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum119
5-th percentile508.25
Q12177.5
median5434
Q314631
95-th percentile83167.6
Maximum173809
Range173690
Interquartile range (IQR)12453.5

Descriptive statistics

Standard deviation28122.43347
Coefficient of variation (CV)1.681621066
Kurtosis8.788483299
Mean16723.40698
Median Absolute Deviation (MAD)4431
Skewness2.840798729
Sum2876426
Variance790871264.5
MonotocityNot monotonic
2022-10-21T10:37:07.650028image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
205710.6%
 
387210.6%
 
315610.6%
 
47610.6%
 
2689310.6%
 
7825310.6%
 
1283510.6%
 
857510.6%
 
995010.6%
 
410310.6%
 
Other values (162)16293.6%
 
ValueCountFrequency (%) 
11910.6%
 
12410.6%
 
13410.6%
 
28010.6%
 
40410.6%
 
ValueCountFrequency (%) 
17380910.6%
 
13223810.6%
 
11503010.6%
 
11176210.6%
 
9974310.6%
 

Women
Real number (ℝ≥0)

HIGH CORRELATION

Distinct171
Distinct (%)99.4%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean22646.67442
Minimum0
Maximum307087
Zeros1
Zeros (%)0.6%
Memory size1.4 KiB
2022-10-21T10:37:08.254655image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile330.95
Q11778.25
median8386.5
Q322553.75
95-th percentile109833.95
Maximum307087
Range307087
Interquartile range (IQR)20775.5

Descriptive statistics

Standard deviation41057.33074
Coefficient of variation (CV)1.81295187
Kurtosis16.39671616
Mean22646.67442
Median Absolute Deviation (MAD)7113.5
Skewness3.593272952
Sum3895228
Variance1685704407
MonotocityNot monotonic
2022-10-21T10:37:08.371421image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
97321.2%
 
1036510.6%
 
45110.6%
 
20910.6%
 
11682510.6%
 
6369810.6%
 
3541110.6%
 
1607510.6%
 
1024810.6%
 
1563210.6%
 
Other values (161)16193.1%
 
ValueCountFrequency (%) 
010.6%
 
7710.6%
 
10910.6%
 
13110.6%
 
13510.6%
 
ValueCountFrequency (%) 
30708710.6%
 
18762110.6%
 
16894710.6%
 
15783310.6%
 
15611810.6%
 

Major_category
Categorical

Distinct16
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Engineering
29 
Education
16 
Humanities & Liberal Arts
15 
Biology & Life Science
14 
Business
13 
Other values (11)
86 
ValueCountFrequency (%) 
Engineering2916.8%
 
Education169.2%
 
Humanities & Liberal Arts158.7%
 
Biology & Life Science148.1%
 
Business137.5%
 
Health126.9%
 
Computers & Mathematics116.4%
 
Physical Sciences105.8%
 
Agriculture & Natural Resources105.8%
 
Social Science95.2%
 
Other values (6)3419.7%
 
2022-10-21T10:37:08.487641image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.6%
2022-10-21T10:37:08.589450image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length14
Mean length16.7283237
Min length4

ShareWomen
Real number (ℝ≥0)

Distinct172
Distinct (%)100.0%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean0.522223365
Minimum0
Maximum0.968953683
Zeros1
Zeros (%)0.6%
Memory size1.4 KiB
2022-10-21T10:37:08.698321image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1331516353
Q10.3360262068
median0.534024037
Q30.7032992108
95-th percentile0.8879201835
Maximum0.968953683
Range0.968953683
Interquartile range (IQR)0.367273004

Descriptive statistics

Standard deviation0.2312049857
Coefficient of variation (CV)0.4427319826
Kurtosis-0.9224765386
Mean0.522223365
Median Absolute Deviation (MAD)0.186895961
Skewness-0.1346841674
Sum89.82241877
Variance0.05345574542
MonotocityNot monotonic
2022-10-21T10:37:08.822070image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.12056434410.6%
 
0.72803259110.6%
 
0.12503465510.6%
 
0.30510948910.6%
 
0.81287660610.6%
 
0.44873230910.6%
 
0.73396758310.6%
 
0.65212981710.6%
 
0.50737696810.6%
 
0.79209526210.6%
 
Other values (162)16293.6%
 
ValueCountFrequency (%) 
010.6%
 
0.07745302710.6%
 
0.09071250910.6%
 
0.10185185210.6%
 
0.10731319610.6%
 
ValueCountFrequency (%) 
0.96895368310.6%
 
0.96799811910.6%
 
0.92780724610.6%
 
0.92374547910.6%
 
0.9109325710.6%
 

Sample_size
Real number (ℝ≥0)

HIGH CORRELATION

Distinct147
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean356.0809249
Minimum2
Maximum4212
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:08.947846image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7
Q139
median130
Q3338
95-th percentile1668.6
Maximum4212
Range4210
Interquartile range (IQR)299

Descriptive statistics

Standard deviation618.3610223
Coefficient of variation (CV)1.736574411
Kurtosis11.9861795
Mean356.0809249
Median Absolute Deviation (MAD)105
Skewness3.192037349
Sum61602
Variance382370.3539
MonotocityNot monotonic
2022-10-21T10:37:09.063015image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3631.7%
 
431.7%
 
731.7%
 
2231.7%
 
42521.2%
 
9521.2%
 
3721.2%
 
15821.2%
 
14221.2%
 
2421.2%
 
Other values (137)14986.1%
 
ValueCountFrequency (%) 
210.6%
 
321.2%
 
431.7%
 
521.2%
 
731.7%
 
ValueCountFrequency (%) 
421210.6%
 
268410.6%
 
258410.6%
 
255410.6%
 
239410.6%
 

Employed
Real number (ℝ≥0)

HIGH CORRELATION

Distinct171
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31192.76301
Minimum0
Maximum307933
Zeros1
Zeros (%)0.6%
Memory size1.4 KiB
2022-10-21T10:37:09.179301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile751.6
Q13608
median11797
Q331433
95-th percentile149243.6
Maximum307933
Range307933
Interquartile range (IQR)27825

Descriptive statistics

Standard deviation50675.00224
Coefficient of variation (CV)1.624575618
Kurtosis9.194017561
Mean31192.76301
Median Absolute Deviation (MAD)9348
Skewness2.863443441
Sum5396348
Variance2567955852
MonotocityNot monotonic
2022-10-21T10:37:09.293391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
212521.2%
 
705221.2%
 
197610.6%
 
1770010.6%
 
343110.6%
 
300710.6%
 
61310.6%
 
11824110.6%
 
10564610.6%
 
3831510.6%
 
Other values (161)16193.1%
 
ValueCountFrequency (%) 
010.6%
 
55910.6%
 
60410.6%
 
61310.6%
 
64010.6%
 
ValueCountFrequency (%) 
30793310.6%
 
27623410.6%
 
19018310.6%
 
18229510.6%
 
18090310.6%
 

Full_time
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26029.30636
Minimum111
Maximum251540
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:09.410896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile702.6
Q13154
median10048
Q325147
95-th percentile129074.6
Maximum251540
Range251429
Interquartile range (IQR)21993

Descriptive statistics

Standard deviation42869.65509
Coefficient of variation (CV)1.64697647
Kurtosis8.765504957
Mean26029.30636
Median Absolute Deviation (MAD)8031
Skewness2.843483682
Sum4503070
Variance1837807328
MonotocityNot monotonic
2022-10-21T10:37:09.531775image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
184910.6%
 
1125910.6%
 
247310.6%
 
48810.6%
 
9840810.6%
 
8468110.6%
 
2934010.6%
 
1435410.6%
 
1400210.6%
 
1009910.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
11110.6%
 
48810.6%
 
52410.6%
 
55610.6%
 
55810.6%
 
ValueCountFrequency (%) 
25154010.6%
 
23320510.6%
 
17138510.6%
 
15666810.6%
 
15196710.6%
 

Part_time
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct170
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8832.398844
Minimum0
Maximum115172
Zeros3
Zeros (%)1.7%
Memory size1.4 KiB
2022-10-21T10:37:09.646411image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile179
Q11030
median3299
Q39948
95-th percentile38185
Maximum115172
Range115172
Interquartile range (IQR)8918

Descriptive statistics

Standard deviation14648.17947
Coefficient of variation (CV)1.658459919
Kurtosis18.30512781
Mean8832.398844
Median Absolute Deviation (MAD)2767
Skewness3.621007516
Sum1528005
Variance214569161.9
MonotocityNot monotonic
2022-10-21T10:37:09.768130image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
031.7%
 
84721.2%
 
27010.6%
 
637710.6%
 
89110.6%
 
18510.6%
 
2955810.6%
 
4065710.6%
 
1456910.6%
 
797810.6%
 
Other values (160)16092.5%
 
ValueCountFrequency (%) 
031.7%
 
12610.6%
 
13310.6%
 
13510.6%
 
15010.6%
 
ValueCountFrequency (%) 
11517210.6%
 
7237110.6%
 
5782510.6%
 
5035710.6%
 
4988910.6%
 

Full_time_year_round
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19694.42775
Minimum111
Maximum199897
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:09.891339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile538.6
Q12453
median7413
Q316891
95-th percentile93263.2
Maximum199897
Range199786
Interquartile range (IQR)14438

Descriptive statistics

Standard deviation33160.94151
Coefficient of variation (CV)1.683772788
Kurtosis9.350771185
Mean19694.42775
Median Absolute Deviation (MAD)5883
Skewness2.92906522
Sum3407136
Variance1099648042
MonotocityNot monotonic
2022-10-21T10:37:10.013915image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
120710.6%
 
807310.6%
 
176310.6%
 
38310.6%
 
7353110.6%
 
5921810.6%
 
2005610.6%
 
880110.6%
 
887110.6%
 
746010.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
11110.6%
 
34010.6%
 
38310.6%
 
38810.6%
 
39110.6%
 
ValueCountFrequency (%) 
19989710.6%
 
17443810.6%
 
13829910.6%
 
12723010.6%
 
12316910.6%
 

Unemployed
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct161
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2416.32948
Minimum0
Maximum28169
Zeros5
Zeros (%)2.9%
Memory size1.4 KiB
2022-10-21T10:37:10.144814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33
Q1304
median893
Q32393
95-th percentile11536.4
Maximum28169
Range28169
Interquartile range (IQR)2089

Descriptive statistics

Standard deviation4112.803148
Coefficient of variation (CV)1.702087063
Kurtosis12.27882716
Mean2416.32948
Median Absolute Deviation (MAD)756
Skewness3.174630334
Sum418025
Variance16915149.73
MonotocityNot monotonic
2022-10-21T10:37:10.263123image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
052.9%
 
8721.2%
 
75721.2%
 
106721.2%
 
30821.2%
 
3321.2%
 
41921.2%
 
28621.2%
 
7821.2%
 
21610.6%
 
Other values (151)15187.3%
 
ValueCountFrequency (%) 
052.9%
 
1110.6%
 
1610.6%
 
2310.6%
 
3321.2%
 
ValueCountFrequency (%) 
2816910.6%
 
2150210.6%
 
1502210.6%
 
1494610.6%
 
1460210.6%
 

Unemployment_rate
Real number (ℝ≥0)

ZEROS

Distinct169
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06819083091
Minimum0
Maximum0.177226407
Zeros5
Zeros (%)2.9%
Memory size1.4 KiB
2022-10-21T10:37:10.390708image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0191376886
Q10.050306435
median0.067960766
Q30.087557114
95-th percentile0.1133826206
Maximum0.177226407
Range0.177226407
Interquartile range (IQR)0.037250679

Descriptive statistics

Standard deviation0.0303309398
Coefficient of variation (CV)0.4447949877
Kurtosis1.007472309
Mean0.06819083091
Median Absolute Deviation (MAD)0.0183129
Skewness0.2956186683
Sum11.79701375
Variance0.0009199659091
MonotocityNot monotonic
2022-10-21T10:37:10.511475image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
052.9%
 
0.01838052710.6%
 
0.01620283510.6%
 
0.02222855510.6%
 
0.09672574310.6%
 
0.05735992910.6%
 
0.09566691210.6%
 
0.07556638610.6%
 
0.08363353110.6%
 
0.05408294110.6%
 
Other values (159)15991.9%
 
ValueCountFrequency (%) 
052.9%
 
0.00633434310.6%
 
0.01168969210.6%
 
0.01620283510.6%
 
0.01838052710.6%
 
ValueCountFrequency (%) 
0.17722640710.6%
 
0.159490610.6%
 
0.15184980710.6%
 
0.14904819810.6%
 
0.12842629910.6%
 

Median
Real number (ℝ≥0)

HIGH CORRELATION

Distinct59
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40151.44509
Minimum22000
Maximum110000
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:10.642293image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum22000
5-th percentile28000
Q133000
median36000
Q345000
95-th percentile60000
Maximum110000
Range88000
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation11470.1818
Coefficient of variation (CV)0.2856729509
Kurtosis7.649279215
Mean40151.44509
Median Absolute Deviation (MAD)4000
Skewness2.036867702
Sum6946200
Variance131565070.6
MonotocityDecreasing
2022-10-21T10:37:10.757189image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
350002011.6%
 
40000179.8%
 
5000095.2%
 
3300095.2%
 
4500095.2%
 
3400084.6%
 
3200084.6%
 
3000084.6%
 
3600063.5%
 
6000063.5%
 
Other values (49)7342.2%
 
ValueCountFrequency (%) 
2200010.6%
 
2340010.6%
 
2500021.2%
 
2600010.6%
 
2700021.2%
 
ValueCountFrequency (%) 
11000010.6%
 
7500010.6%
 
7300010.6%
 
7000010.6%
 
6500021.2%
 

P25th
Real number (ℝ≥0)

Distinct48
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29501.44509
Minimum18500
Maximum95000
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:10.873553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum18500
5-th percentile20000
Q124000
median27000
Q333000
95-th percentile45000
Maximum95000
Range76500
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation9166.005235
Coefficient of variation (CV)0.3106968221
Kurtosis14.51491312
Mean29501.44509
Median Absolute Deviation (MAD)4000
Skewness2.728044969
Sum5103750
Variance84015651.97
MonotocityNot monotonic
2022-10-21T10:37:10.990092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%) 
250002212.7%
 
300001810.4%
 
24000126.9%
 
20000116.4%
 
23000105.8%
 
2700074.0%
 
3500063.5%
 
2200052.9%
 
2600052.9%
 
2800052.9%
 
Other values (38)7241.6%
 
ValueCountFrequency (%) 
1850010.6%
 
1920031.7%
 
20000116.4%
 
2080010.6%
 
2100042.3%
 
ValueCountFrequency (%) 
9500010.6%
 
5500010.6%
 
5300010.6%
 
5000042.3%
 
4800010.6%
 

P75th
Real number (ℝ≥0)

HIGH CORRELATION

Distinct54
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51494.21965
Minimum22000
Maximum125000
Zeros0
Zeros (%)0.0%
Memory size1.4 KiB
2022-10-21T10:37:11.115943image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum22000
5-th percentile35600
Q142000
median47000
Q360000
95-th percentile75400
Maximum125000
Range103000
Interquartile range (IQR)18000

Descriptive statistics

Standard deviation14906.27974
Coefficient of variation (CV)0.2894748156
Kurtosis4.97931887
Mean51494.21965
Median Absolute Deviation (MAD)7000
Skewness1.816489279
Sum8908500
Variance222197175.7
MonotocityNot monotonic
2022-10-21T10:37:11.239217image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
450001810.4%
 
500001810.4%
 
40000179.8%
 
42000116.4%
 
60000116.4%
 
7000063.5%
 
4100063.5%
 
6500063.5%
 
3500063.5%
 
3800052.9%
 
Other values (44)6939.9%
 
ValueCountFrequency (%) 
2200010.6%
 
2600010.6%
 
3400010.6%
 
3500063.5%
 
3600010.6%
 
ValueCountFrequency (%) 
12500010.6%
 
10900010.6%
 
10500010.6%
 
10200010.6%
 
9000021.2%
 

College_jobs
Real number (ℝ≥0)

UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12322.63584
Minimum0
Maximum151643
Zeros1
Zeros (%)0.6%
Memory size1.4 KiB
2022-10-21T10:37:11.365038image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile444.8
Q11675
median4390
Q314444
95-th percentile42789.4
Maximum151643
Range151643
Interquartile range (IQR)12769

Descriptive statistics

Standard deviation21299.86886
Coefficient of variation (CV)1.728515647
Kurtosis17.48266034
Mean12322.63584
Median Absolute Deviation (MAD)3646
Skewness3.77129362
Sum2131816
Variance453684413.6
MonotocityNot monotonic
2022-10-21T10:37:11.480588image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
153410.6%
 
1069910.6%
 
109610.6%
 
35510.6%
 
8200710.6%
 
3533610.6%
 
1505110.6%
 
495610.6%
 
1092810.6%
 
522510.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
010.6%
 
16210.6%
 
22110.6%
 
28810.6%
 
34610.6%
 
ValueCountFrequency (%) 
15164310.6%
 
12514810.6%
 
10808510.6%
 
8823210.6%
 
8200710.6%
 

Non_college_jobs
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct173
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13284.49711
Minimum0
Maximum148395
Zeros1
Zeros (%)0.6%
Memory size1.4 KiB
2022-10-21T10:37:11.603274image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile242.6
Q11591
median4595
Q311783
95-th percentile65146.4
Maximum148395
Range148395
Interquartile range (IQR)10192

Descriptive statistics

Standard deviation23789.65536
Coefficient of variation (CV)1.790783284
Kurtosis12.90542129
Mean13284.49711
Median Absolute Deviation (MAD)3917
Skewness3.377170775
Sum2298218
Variance565947702.3
MonotocityNot monotonic
2022-10-21T10:37:11.719767image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
36410.6%
 
197710.6%
 
169210.6%
 
14410.6%
 
3111210.6%
 
5456910.6%
 
1819310.6%
 
1034310.6%
 
556110.6%
 
738510.6%
 
Other values (163)16394.2%
 
ValueCountFrequency (%) 
010.6%
 
5010.6%
 
6710.6%
 
10210.6%
 
14410.6%
 
ValueCountFrequency (%) 
14839510.6%
 
14186010.6%
 
10083110.6%
 
9796410.6%
 
9388910.6%
 

Low_wage_jobs
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct166
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3859.017341
Minimum0
Maximum48207
Zeros5
Zeros (%)2.9%
Memory size1.4 KiB
2022-10-21T10:37:11.839857image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49.6
Q1340
median1231
Q33466
95-th percentile17465
Maximum48207
Range48207
Interquartile range (IQR)3126

Descriptive statistics

Standard deviation6944.998579
Coefficient of variation (CV)1.799680583
Kurtosis13.32662508
Mean3859.017341
Median Absolute Deviation (MAD)1039
Skewness3.338072027
Sum667610
Variance48233005.26
MonotocityNot monotonic
2022-10-21T10:37:11.960196image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
052.9%
 
8121.2%
 
26321.2%
 
30821.2%
 
1144310.6%
 
1683910.6%
 
526710.6%
 
316810.6%
 
180610.6%
 
185410.6%
 
Other values (156)15690.2%
 
ValueCountFrequency (%) 
052.9%
 
2510.6%
 
3110.6%
 
3710.6%
 
4910.6%
 
ValueCountFrequency (%) 
4820710.6%
 
3239510.6%
 
2833910.6%
 
2796810.6%
 
2744010.6%
 

Interactions

2022-10-21T10:36:30.303612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:30.555996image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:30.657674image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:30.757542image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:30.853204image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:30.945658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.036694image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.127765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.226935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.324473image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.421727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.576617image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.685257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.782571image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.875546image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:31.969871image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.060028image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.152097image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.243524image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.341496image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.438029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.536239image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.626088image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.717262image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.815199image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.899154image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:32.985246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.264087image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.351814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.443460image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.545961image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.628614image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.716592image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.798297image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.886237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:35.969761image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.055304image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.140696image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.223727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.316662image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.406230image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.501921image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.596160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.689065image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.779447image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.869769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:36.962583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.051296image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.144272image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.241416image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.329822image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.438863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.527139image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.625291image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.716684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.811910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.908259image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:37.998978image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.087076image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.173581image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.378432image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.470401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.559133image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.644790image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.729699image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.819872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.908043image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:38.998263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.093597image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.179311image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.270626image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.354994image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.445481image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.532258image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.621579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.718084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.807808image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.893429image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:39.979590image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.073069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.162358image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.249712image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.333989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.415744image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.502536image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.585217image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.671291image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.762772image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.845545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:40.935606image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.016428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.105087image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.188549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.277394image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.366734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.450008image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.533406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.615115image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.702531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.788254image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:41.871661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.087583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.168163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.253139image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.335373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.417611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.506585image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.588011image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.673939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.753278image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.837203image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:42.919073image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.004332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.089938image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.171038image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.249834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.332620image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.425286image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.510574image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.592320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.673585image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.750395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.831789image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.918134image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:43.997568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.083469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.161033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.245851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.320661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.401151image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.477619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.560315image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.647041image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.725075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.816272image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.899776image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:44.988727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.077148image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.163257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.248391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.337882image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.424521image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.516244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.606648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.698427image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.782801image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.873199image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:45.959693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.051792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.139029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.231905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.328272image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.419315image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.777917image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.860803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:46.951957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.035652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.118548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.199045image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.279322image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.362466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.443730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.526187image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.613824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.696771image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.782804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.861461image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:47.948975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.028946image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.115677image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.204436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.287763image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.373847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.459069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.551648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.639709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.728134image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.813383image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.897233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:48.982784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.070769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.157211image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.251986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.337022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.427525image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.509603image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.599805image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.684940image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.779415image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.871867image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:49.957168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.050723image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.144084image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.243179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.338798image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.434768image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.526977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.617888image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.715062image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.805489image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:50.899685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.000171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.094741image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.191641image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.281750image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.381571image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.473157image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.572007image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.670507image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.765269image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.855296image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:51.937649image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.024098image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.109684image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.191063image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.468971image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.551205image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.633612image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.715435image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.798792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.886666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:52.979062image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.063531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.144248image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.230401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.311608image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.399897image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.487590image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.570050image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.662956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.753167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.849670image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:53.944138image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.036660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.126068image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.213848image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.304908image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.395000image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.487192image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.584965image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.678492image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.774472image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.864148image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:54.958038image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.046597image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.141109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.236207image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.330265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.411100image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.488380image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.572484image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.654022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.737233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.815635image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.891190image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:55.972601image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.051320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.131669image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.223604image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.303673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.387532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.463159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.546203image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.623501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.706556image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.789396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.866811image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:56.959713image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.047651image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.141168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.232842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.322657image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.411332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.497813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.588880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.677298image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.767168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.877091image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:57.965440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.059681image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.145732image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.237667image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.325640image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.417903image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.511252image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.600110image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.684172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.766116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.853544image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:58.939280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.022225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.103758image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.428913image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.512733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.594607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.677747image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.769014image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.850250image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:36:59.938763image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.018646image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.104369image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.190019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.282859image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.369994image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.452185image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.542689image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.635109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.730105image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.826209image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:00.917727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.008192image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.095952image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.187925image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.277067image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.368072image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.470416image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.566664image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.659976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.745977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.839069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:01.926879image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.017616image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.108549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.196618image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.286215image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.373315image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.466792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.558749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.648503image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.736280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.822523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:02.942504image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.036474image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.128385image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.254516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.347507image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.444161image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.533606image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.626337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.714696image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.807419image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.901244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:03.988820image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.071354image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.157109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.244907image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.330459image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.415376image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.496531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.576077image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.661443image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.743288image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.826777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.916040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:04.996092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.081863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.161650image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.249141image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.336625image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.427288image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:05.513892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-10-21T10:37:12.084792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-10-21T10:37:12.285213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-10-21T10:37:12.479672image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-10-21T10:37:12.682905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-10-21T10:37:05.703405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:06.036340image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:06.201016image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-10-21T10:37:06.295791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Sample

First rows

RankMajor_codeMajorTotalMenWomenMajor_categoryShareWomenSample_sizeEmployedFull_timePart_timeFull_time_year_roundUnemployedUnemployment_rateMedianP25thP75thCollege_jobsNon_college_jobsLow_wage_jobs
012419PETROLEUM ENGINEERING2339.02057.0282.0Engineering0.12056436197618492701207370.018381110000950001250001534364193
122416MINING AND MINERAL ENGINEERING756.0679.077.0Engineering0.1018527640556170388850.11724175000550009000035025750
232415METALLURGICAL ENGINEERING856.0725.0131.0Engineering0.1530373648558133340160.02409673000500001050004561760
342417NAVAL ARCHITECTURE AND MARINE ENGINEERING1258.01123.0135.0Engineering0.107313167581069150692400.0501257000043000800005291020
452405CHEMICAL ENGINEERING32260.021239.011021.0Engineering0.341631289256942317051801669716720.061098650005000075000183144440972
562418NUCLEAR ENGINEERING2573.02200.0373.0Engineering0.144967171857203826414494000.17722665000500001020001142657244
676202ACTUARIAL SCIENCE3777.02110.01667.0Business0.441356512912292429624823080.0956526200053000720001768314259
785001ASTRONOMY AND ASTROPHYSICS1792.0832.0960.0Physical Sciences0.5357141015261085553827330.0211676200031500109000972500220
892414MECHANICAL ENGINEERING91227.080320.010907.0Engineering0.11955910297644271298131015463946500.05734260000480007000052844163843253
9102408ELECTRICAL ENGINEERING81527.065511.016016.0Engineering0.1964506316192855450126954141338950.05917460000450007200045829108743170

Last rows

RankMajor_codeMajorTotalMenWomenMajor_categoryShareWomenSample_sizeEmployedFull_timePart_timeFull_time_year_roundUnemployedUnemployment_rateMedianP25thP75thCollege_jobsNon_college_jobsLow_wage_jobs
1631646102COMMUNICATION DISORDERS SCIENCES AND SERVICES38279.01225.037054.0Health0.967998952976319975138621446014870.0475842800020000400001995794045125
1641652307EARLY CHILDHOOD EDUCATION37589.01167.036422.0Education0.968954342325512756970012074813600.0401052800021000350002351577052868
1651662603OTHER FOREIGN LANGUAGES11204.03472.07732.0Humanities & Liberal Arts0.6901115670525197368532148460.107116275002290038000232637031115
1661676001DRAMA AND THEATER ARTS43249.014440.028809.0Arts0.6661193573616525147159941689130400.07754127000192003500069942531311068
1671683302COMPOSITION AND RHETORIC18953.07022.011931.0Humanities & Liberal Arts0.62950515115053101216612783213400.081742270002000035000485581003466
1681693609ZOOLOGY8409.03050.05359.0Biology & Life Science0.6372934762595043219036023040.04632026000200003900027712947743
1691705201EDUCATIONAL PSYCHOLOGY2854.0522.02332.0Psychology & Social Work0.81709972125184857212111480.065112250002400034000148861582
1701715202CLINICAL PSYCHOLOGY2838.0568.02270.0Psychology & Social Work0.799859132101172464812933680.149048250002500040000986870622
1711725203COUNSELING PSYCHOLOGY4626.0931.03695.0Psychology & Social Work0.798746213777315496527382140.05362123400192002600024031245308
1721733501LIBRARY SCIENCE1098.0134.0964.0Education0.8779602742593237410870.104946220002000022000288338192